Detection Of Discontinuities Research Articles

A neural network based shock detection and localization approach for discontinuous Galerkin methods

The stable and accurate approximation of discontinuities such as shocks on a finite computational mesh is a challenging task. Detection of shocks or strong discontinuities in the flow solution is typically achieved through a priori troubled cell indicators, which guide the subsequent action of an appropriate shock capturing mechanism. Arriving at a stable and accurate solution often requires empirically based parameter tuning and adjustments of the indicator settings to the discretization and solution at hand. In this work, we propose to separate the task of shock detection and shock capturing more strongly and aim to develop a shock indicator that is robust, accurate, requires minimal user input and is suitable for high order element-based methods like discontinuous Galerkin and flux reconstruction methods. The novel indicator is learned from analytical data through a supervised learning strategy; its input is given by the high order solution field, its output is an element-local map of the shock position. We use state of the art methods from edge detection in image analysis based on deep convolutional multiscale networks and deep supervision to train the indicators. The resulting networks are then used as black box indicators, showing their robustness and accuracy on well established canonical testcases. All simulations are run ab initio using the developed indicators, showing that they provide also stability during the strongly transient phases. In particular for high order schemes with large cells and considerable inner-cell resolution capabilities, we demonstrate how the additional accurate prediction of the position of the shock front can be exploited to guide inner-element shock capturing strategies.

A Cooperative Approach Based on Local Detection of Similarities and Discontinuities for Brain MR Images Segmentation.

This paper introduces a new cooperative multi-agent approach for segmenting brain Magnetic Resonance Images (MRIs). MRIs are manually processed by human radiology experts for the identification of many diseases and the monitoring of their evolution. However, such a task is time-consuming and depends on expert decision, which can be affected by many factors. Therefore, various types of research were and are still conducted to automate MRI processing, mainly MRI segmentation. The approach presented in this paper, without any parametrization or prior knowledge, uses a set of situated agents, locally interacting to segment images according to two main phases: the detection of discontinuities and the detection of similarities. An implementation of this approach was tested on phantom brain MR images to assess the results and prove its efficiency. Experimental results ensure a minimum of 89% Dice coefficient with increasing values of the noise and the intensity non-uniformity.

A Novel Finite-Element-Based Algorithm for Damage Detection in the Pressure Vessels Using the Wavelet Approach

In this investigation a suitable algorithm for the detection of cracks in the pressure vessels is presented. The equations of motion for the vessel are obtained and transferred into the wavelet space in a simplified form resulted from time and position approximations. The locations of cracks are randomly distributed in different regions of the structure to cover the whole geometry of the pressure vessel. Furthermore, the pressure vessel is installed vertically with a fixed end at the bottom of each of its four leg supports. Then, the results are transferred to the wavelet space using Daubechies wavelet families. From the comparison of the displacement results associated with the intact and damaged vessels, it can be clearly seen that the crack location can be accurately detected noting the alteration in the wavelet output diagrams .The results of the crack detection show that with the proper selection of the wavelet type, the wavelet based finite element method is a suitable and nondestructive method as well as a powerful numerical tool for the detection of cracks and other discontinuities in the pressure vessels. The results of this investigation can be used in the marine and aerospace industries as well as power stations.

Multi-modal RGB-D Image Segmentation from Appearance and Geometric Depth Maps

Classical image segmentation algorithms exploit the detection of similarities and discontinuities of different visual cues to define and differentiate multiple regions of interest in images. However, due to the high variability and uncertainty of image data, producing accurate results is difficult. In other words, segmentation based just on color is often insufficient for a large percentage of real-life scenes. This work presents a novel multi-modal segmentation strategy that integrates depth and appearance cues from RGB-D images by building a hierarchical region-based representation, i.e., a multi-modal segmentation tree (MM-tree). For this purpose, RGB-D image pairs are represented in a complementary fashion by different segmentation maps. Based on color images, a color segmentation tree (C-tree) is created to obtain segmented and over-segmented maps. From depth images, two independent segmentation maps are derived by computing planar and 3D edge primitives. Then, an iterative region merging process can be used to locally group the previously obtained maps into the MM-tree. Finally, the top emerging MM-tree level coherently integrates the available information from depth and appearance maps. The experiments were conducted using the NYU-Depth V2 RGB-D dataset, which demonstrated the competitive results of our strategy compared to state-of-the-art segmentation methods. Specifically, using test images, our method reached average scores of 0.56 in Segmentation Covering and 2.13 in Variation of Information.

Automated Discontinuity Detection and Reconstruction in Subsurface Environment of Mars Using Deep Learning: A Case Study of SHARAD Observation

Machine learning (ML) algorithmic developments and improvements in Earth and planetary science are expected to bring enormous benefits for areas such as geospatial database construction, automated geological feature reconstruction, and surface dating. In this study, we aim to develop a deep learning (DL) approach to reconstruct the subsurface discontinuities in the subsurface environment of Mars employing the echoes of the Shallow Subsurface Radar (SHARAD), a sounding radar equipped on the Mars Reconnaissance Orbiter (MRO). Although SHARAD has produced highly valuable information about the Martian subsurface, the interpretation of the radar echo of SHARAD is a challenging task considering the vast stocks of datasets and the noisy signal. Therefore, we introduced a 3D subsurface mapping strategy consisting of radar echo pre-processors and a DL algorithm to automatically detect subsurface discontinuities. The developed components the of DL algorithm were synthesized into a subsurface mapping scheme and applied over a few target areas such as mid-latitude lobate debris aprons (LDAs), polar deposits and shallow icy bodies around the Phoenix landing site. The outcomes of the subsurface discontinuity detection scheme were rigorously validated by computing several quality metrics such as accuracy, recall, Jaccard index, etc. In the context of undergoing development and its output, we expect to automatically trace the shapes of Martian subsurface icy structures with further improvements in the DL algorithm.

Research of Defectoscopic Properties of Powder Compositions for Increasing Efficiency and Reliability of Penetrant Testing of Complex Shaped Parts

Research has been carried out to assess the defectoscopic properties of various compositions of powder preparations in order to determine whether they can be used as part of a modern Russian set of defectoscopic materials for luminescent penetrant testing that ensures detection of discontinuities with sensitivity class 1 as per GOST (State Standard) 18442. To improve the efficiency and reliability of flaw detection in hard-to-reach places of complex shaped parts, compositions have been selected that increase the brightness, contrast, and stability of the indication pattern to mechanical action due to high rates of adsorptive and adhesive interactions of the used penetrant fluid and the surface of the tested part.

Research on Parking Slot Tracking Algorithm Based on Fusion of Vision and Vehicle Chassis Information

During parking, the vision-based parking slot detection system has error or missed detection due to distortion, illumination variation, occlusion and limited field of view (FOV). Thus, the parking slot position sent to path planning system is inaccurate and discontinuous. Besides, the intelligent parking system (IPS) primarily relies on dead reckoning to send vehicle position to the motion control system, whereas the error will accumulate with the rise in driving distance. All the mentioned factors will cause parking deviation, incline or even line-pressing. In this paper, the idea of visual simultaneous localization and mapping (SLAM) is adopted innovatively to achieve the parking slot tracking. Moreover, the extended Kalman filter (EKF) is used to achieve the fusion of vision and vehicle chassis information, to solve the two problems of discontinuous and inaccurate parking slot detection, as well as cumulative error in dead reckoning. Finally, the effectiveness of the proposed algorithm is verified using the vehicle tests.

Comparative Detectability of Planar Extended Defects of Sheet Metal by Reflection and Transmission Methods

Introduction. Currently, sheet metal is the main structural material for multi-purpose use. The actual task of the industry is to improve the quality of rolled sheet. It allows to ensure the necessary reliability of structures and products of especially critical use. The regulatory documents currently in force allow an ultrasonic testing of sheet metal by reflection or by transmission method. Due to lack of specific recommendations it becomes unclear which of the methods is preferable to use. Aim. An estimation of the maximum detectability of rolled sheet planar extended defects by reflection methods (echo method) and by transmission methods (shadow and mirror-shadow methods). Materials and methods . Based on analysis of the equations of acoustic paths, formulas were determined. The formulas allow one to evaluate an ultimate detectability of planar discontinuities of plate rolling by echo, shadow and mirror-shadow methods in a contact version by longitudinal waves. Experimental studies were conducted under computer simulation using the Mathcad mathematical package. Results. Integral expressions for calculating of amplitudes of echo signal from a plane defect, of bottom signal in defect-free and defective areas and their ratio for the echo method were obtained. The expressions for calculating of amplitudes of transmitted and bottom signals in defective and defect-free areas and their ratio for shadow and mirror-shadow methods were determined. Based on the numerical analysis, an estimation of the maximum detectability of planar extended defects of sheet metal was realized. It is possible to detect defects with a thickness of 5 pm by reflection methods and with a thickness more than 100 pm by transmission methods. Conclusion . It was established that reflection methods have better capabilities for detecting plane defects by longitudinal waves. The conditions for reducing of the thickness of the equivalent layer associated with an increase in transducers wave size were determined. It was shown that in order to detect defects with a small thickness, it is more expedient to give preference to the echo method of ultrasonic testing.

Evolution of the landscape and pedodiversity on volcanic deposits in the south of the Basin of Mexico and its relationship with agricultural activities.

In this work, we present the results of a soil study in the Teuhtli volcano, located to the south of the Basin of Mexico with the aim to understand the pedogenetic pathways and the evolution of the landscape dynamics. Two different types of soil prof iles were sampled: in “conserved” areas, with less anthropogenic influence and in sites with intense agriculture activities since pre-Hispanic times. The three conserved prof iles are located in different landscape positions: the Cima prof ile in the summit, the Ladera prof ile in the high slope, and the Yotecón in a lower position of the piedemont. The agriculture prof iles are La Cruz, La Era and El Llano, situated in the foothill. Properties in both kind of soils are similar, however, in agriculture sites, structure (evaluated in macro and microscale) is weaker, total organic carbon content is smaller and bulk density is higher. Both soils show two main pedogenetic processes: andosolization and carbonate formation. Despite the age of the parent material (36 000 years), the Andosol phase has not been lost. This is because of the geomorphological dynamics of the zone, in which the processes of erosion and colluviation promote soil loss, restarting the pedogenetic clock. The detection of lithological discontinuities (by the Ti/Zr ratio) documents these processes. By the other hand, the formation of pedogenic carbonates is governed by the seasonal conditions of drought. The age of these carbonates places their formation in the mid-Holocene, an epoch for which drier conditions are detected in other sites of the Basin of Mexico. The agricultural land use has also promoted morphological, chemical and physical changes in the soils. The continuous tillage of the sites has prevented the soils from developing. This could have a negative effect on the fertility of those soils currently used to sustain the peri-urban agroecosystems of Mexico City.

Characterisation of Friction Stir Weld Discontinuities by Non-destructive Evaluation

Friction stir weld (FSW) is an advanced metal joining process recently practised in aerospace industries with application spanning across other engineering fields as well. Friction stir welding being solid-state joining process, the weld is characterised by superior weld properties with proper parameter setting. The morphology of FSWs varies from other welds due to the plastic state formation of the material as against the liquid state of fusion encountered in conventional welding process. The nature of the discontinuities in these joints is significantly different. The presence of discontinuities in the welds due to its unique weld formation process has made the failure pattern in these products also unique. Hence, a comprehensive non-destructive evaluation (NDE) assessment of FSWs is attempted with different techniques and their detecting capability has been discussed. Conventional NDE methods, namely radiography, ultrasonics and eddy current techniques used in FSW discontinuity detection are discussed and compared for each type of discontinuity.

Crack detection in a shaft using finite difference technique

Fatigue cracks arise in a rotor shaft due to cyclic loading. A growing crack in a machine element may lead to a calamitous failure of the machinery. Identification of crack at an early stage supports in safe and economic running of machinery. The appearance of crack in a shaft reduces local stiffness and causes a slope discontinuity in the shaft elastic line during vibration. Detection of slope discontinuity reveals the presence of crack in a shaft. However, in the presence of measurement noise, identification of slope discontinuity is difficult. In the present work, finite element model of a cracked simply supported shaft is considered for the simulation work. A transverse surface crack is considered for the cracked model. The shaft is assumed to be non-rotating and an external sinusoidal forcing is used to excite the shaft. To imitate actual experimentation, Gaussian noise is added in the simulated cracked shaft response. A dominant peak is observed at the crack position, which is obtained by using the central finite difference approximation on the simulated response of simply supported shaft. The method is used for the localization of the cracks present in the shaft. It is based on detecting the slope discontinuity in the elastic line of the shaft. The finite difference method based evaluation is also implemented for varying crack depth ratios at different signal to noise ratio (SNR).

Extraction of metamaterial constitutive parameters based on data-driven discontinuity detection

This paper presents an efficient data-driven method to extract the effective metamaterial parameters unambiguously. This method is based on detecting the discontinuity points in the real part of the refractive index and discerning the correct branch values at these discontinuities. The proposed method is numerically simple and does not require an infinite frequency integration. The performance of the proposed method is demonstrated by investigating thin and thick homogenous and periodically structured metamaterial slabs. This method attains correct values of the branch index and, hence, correct values of the refractive index at the entire frequency range for thin and thick slabs independently from its imaginary part. It, notably, succeeds in overcoming the frequency and dimension limits and saturation observed in the Kramers–Kronig (K–K) method in thick homogeneous and multi-cell periodically structured slabs. The proposed method also gives accurate values for the metamaterial parameters at resonance and at the negative parameter region.

Multi-sparsity-based spectral attributes for discontinuity detection

Structural and stratigraphic discontinuities, such as faults and channels, generally contribute to the construction of traps and reservoirs. Spectral decomposition can utilize the sensitivities of different frequency components to different geological conditions to identify these geological anomalies. The sparse inverse spectral decomposition (SISD) involves a sparse constraint of time–frequency spectra, and one critical parameter is the sparsity which determines the time–frequency resolution. A small sparsity gives a low temporal resolution result that cannot be used for thin-bed detection. Conversely, a large sparsity provides a high-resolution result, but it may lose weak reflection signals. The complex geological conditions in the subsurface will lead to some difficulties in detecting the discontinuities by using the SISD method with a fixed sparsity. To address this issue, we propose multi-sparsity-based spectral attributes by fusing the amplitude spectra results of three different sparsities to detect subsurface discontinuities. Compared with the fixed sparsity, the multi-sparsity-based spectral attributes can detect more geological details and highlight geological edges more clearly. The application on a 3D real data with an area of 230 km2 from deep formation in Northwest China exhibits its effectiveness in discontinuity detection. The proposed method can detect the weak or small hidden geological details more and better than the fixed sparsity method, suggesting that it may serve as a future tool for detecting the distribution of geological abnormalities in subsurface.

Level set methods for stochastic discontinuity detection in nonlinear problems

Stochastic problems governed by nonlinear conservation laws are challenging due to solution discontinuities in stochastic and physical space. In this paper, we present a level set method to track discontinuities in stochastic space by solving a Hamilton-Jacobi equation. By introducing a speed function that vanishes at discontinuities, the iso-zeros of the level set problem coincide with the discontinuities of the conservation law. The level set problem is solved on a sequence of successively finer grids in stochastic space. The method is adaptive in the sense that costly evaluations of the conservation law of interest are only performed in the vicinity of the discontinuities during the refinement stage. In regions of stochastic space where the solution is smooth, a surrogate method replaces expensive evaluations of the conservation law. The proposed method is tested in conjunction with different sets of localized orthogonal basis functions on simplex elements, as well as frames based on piecewise polynomials conforming to the level set function. The performance of the proposed method is compared to existing adaptive multi-element generalized polynomial chaos methods.

Detection of lateral discontinuities via surface waves analysis: A case study at a derelict industrial site

We applied a multi-offset surface wave analysis (MOPA) to detect subsoil lateral heterogeneities at a dismissed industrial site along the coast of the city of Trieste (Italy). The site is heavily contaminated and is undergoing characterization in view of possible remediation and re-use. Sea/land interactions and massive anthropic interventions make the site particularly complex. The main lateral heterogeneities consist of an extended buried quay, which also divides continental and marine sediments. We used seismic surface waves to define this contact, while also using supporting data from boreholes and geo-electrical surveys. A multi-offset phase and attenuation analysis was conducted on a few seismic lines, and produced clear evidence concerning the sought heterogeneities. Field data interpretation was corroborated also by ancillary information, and by synthetic modeling, that produced seismograms totally consistent with the recorded ones. In summary, the case study demonstrates how MOPA can be applied in a straightforward manner to define heterogeneities even at a very small spatial scale, and in complex environments such as derelict industrial sites.

A semantic discontinuity detection (SDD) method for comparing designers' product expressions with users' product impressions

Designers exert substantial effort to define an intended user experience (UX) for a product, service or system. However, discontinuities can arise when the actual UX of users differs from the design intent. This paper presents a ‘Semantic Discontinuity Detection’ (SDD) method capable of locating discontinuities between (i) realized product semantics, based on users' initial visual impression of a product, and (ii) intended product semantics, based on the originating designer's visual product expression. The experimental design includes a new technique termed ‘Semantic Network Clustering’ (SNC) to organize diverse product appraisal lexicon. Data generated by the method provides evidence to assist re-designing for reduced semantic discontinuity. The method is suggested to be suitably agile for a wide range of UX intent-realization research.

Detection and geometric characterization of rock mass discontinuities using a 3D high-resolution digital outcrop model generated from RPAS imagery – Ormea rock slope, Italy

The use of a remotely piloted aircraft system (RPAS) and digital photogrammetry is valuable for the detection of discontinuities in areas where field mapping and terrestrial photogrammetry or laser scanner surveys cannot be employed because the slope is unsafe, inaccessible, or characterized by a complex geometry with areas not visible from the ground. Using the Structure-from-Motion method, the acquired images can be used to create a 3D texturized digital outcrop model (TDOM) and a detailed point cloud representing the rock outcrop. Discontinuity orientations in a complex rock outcrop in Italy were mapped in the field using a geological compass and by manual and automated techniques using a TDOM and point cloud generated from RPAS imagery. There was a good agreement between the field measurements and manual mapping in the TDOM. Semi-automated discontinuity mapping using the point cloud was performed using the DSE, qFacet FM, and qFacet KD-tree methods applied to the same 3D model. Significant discrepancies were found between the semi-automatic and manual methods. In particular, the automatic methods did not adequately detect discontinuities that are perpendicular to the slope face (bedding planes in the case study). These differences in detection of discontinuities can adversely influence the kinematic analysis of potential rock slope failure mechanisms. We use the case study to demonstrate a workflow that can accurately map discontinuities with results comparable to field measurements. The combined use of TDOM and RPAS dramatically increases the discontinuity data because RPAS can supply a good coverage of inaccessible or hidden portions of the slope and TDOM is a powerful representation of the reality that can be used to map discontinuity orientations including those that are oriented perpendicular to the slope.

Application of Ground Penetrating Radar (GPR) to Detect Joints in Organic Soft Rock

Abstract The detection of joints and discontinuities is of particular importance to the stability of a broad range of geostructures, including slopes and underground and open-pit mines. As a common example, the mechanical response of soft rocks observed within open-pit mines is significantly influenced by the existence of joint networks, resulting in a complex stress distribution that governs the stability factor of safety as well as the failure mechanism. In this article, surface geophysics scanning by ground penetrating radar (GPR) is presented for the detection of vertical joints at one of the largest open-pit coal mines in Australia. The optimum soil velocity, point interval, and antenna frequency for joint detection in Victorian Brown Coal (VBC) are presented in comparison with electromagnetic properties of known organic soils. Furthermore, the performance of an assorted set of post-processing signal filtering techniques to successfully identify the underground coal fractures are detailed, along with obstructions affecting the feasibility of GPR vertical joint discovery in this light organic soft rock.

Geochemical Detection of Soil Discontinuities in a Relatively Stable Terrain: Wonu, South-West Nigeria

Movement of soil materials resulting in transported overburden occur in relatively stable terrains as described from the Wonu area of South-West Nigeria. The effect of such transported soils may be serious in pedogeochemical studies as they could lead to false anomalies, masked anomalies and incorrect bedrock identification during geological mapping in highly weathered terrains. Several techniques and parameters have been successfully used to detect discontinuities in soil. A lot of these are based on ‘abrupt changes’ expressed by a departure in depth trends mostly physical between zones of otherwise relative uniformity. This study shows that plots of bases/alumina versus silica/alumina from geochemical analysis can be used to separate the transported soil material from that of the soil formed in-situ. Keywords: Lithologic discontinuities, pedogeochemistry, bedrock, anomalies, profile DOI : 10.7176/JNSR/9-3-02

Tracking Poisson Parameter for Non-Stationary Discontinuous Time Series with Taylor’s Abnormal Fluctuation Scaling

We propose a parameter estimation method for non-stationary Poisson time series with the abnormal fluctuation scaling, known as Taylor’s law. By introducing the effect of Taylor’s fluctuation scaling into the State Space Model with the Particle Filter, the underlying Poisson parameter’s time evolution is estimated correctly from given non-stationary time series data with abnormally large fluctuations. We also developed a discontinuity detection method which enables tracking the Poisson parameter even for time series including sudden discontinuous jumps. As an example of application of this new general method, we analyzed Point-of-Sales data in convenience stores to estimate change of probability of purchase of commodities under fluctuating number of potential customers. The effectiveness of our method for Poisson time series with non-stationarity, large discontinuities and Taylor’s fluctuation scaling is verified by artificial and actual time series.